"sede principale"@it . "in dataset" . "Title"@en . . . . . "50" . . "sotto-Organization di"@it . . "has site"@en . . . . _:Na5d9534b36874c589b3ac76ba70ea8a5 . . _:N5a9dd89ba85e48d1aeabc4064b0d8579 . _:N3be0ae7459e0464dafc36181f66f5d7d . "GBP" . . _:Na5d9534b36874c589b3ac76ba70ea8a5 "Wellington Square" . . _:N4bc8bc916c9c4033af45b99da5b65598 "Parks Road" . "45585"^^ . . . "es suborganización de"@es . . . "tiene sede principal en"@es . . "00000000"^^ . "Title"@en . _:N3be0ae7459e0464dafc36181f66f5d7d "Parks Road" . . . . "Agent" . "label" . "preferred label"@en . . "Voice"@en . "Document" . . . . "HTML description of Research Software Engineer (ML)" . . "building" . _:N5a9dd89ba85e48d1aeabc4064b0d8579 . "locality"@en . "based near" . . . "Wolfson Building" . "type" . "COMDL" . _:N3be0ae7459e0464dafc36181f66f5d7d "Oxford" . . . "street address"@en . . "way/197021482" . . . . . . . . . . """_________________________________________________________________________ University of Oxford Department of Computer Science Job description and selection criteria Job title Research Software Engineer (Machine Learning) Division Mathematical, Physical and Life Sciences (MPLS) Department Computer Science Location Wolfson Building, Parks Road, Oxford. Grade and salary Grade 8: £45,585 - £54,395 p.a. with the potential to under-fill at Grade 7 with salaries in the range of £36,024 - £44,263 p.a. Hours Full time (Part time can be considered) Contract type Fixed-term contract until 1 April 2027 Reporting to Professor Andrew Markham, Computer Science Vacancy Reference 173378 Additional information Whilst the role is a grade 8 position, we would be willing to consider candidates with potential but less experience who are seeking a development opportunity, for which an initial appointment would be at Grade 7 (£36,024 - £44,263 p.a.) with the responsibilities adjusted accordingly. This would be discussed with applicants at interview/appointment where appropriate. Research topic Machine Learning Engineer Principal Investigator / Professor Andrew Markham (Computer Science), Professor Andrew supervisor Loveridge (Biology) Funding partner The funds supporting this research project are provided by NERC under the MorphoCam project Overview of the role A cross-disciplinary project between the Departments of Computer Science and Biology has a new opening for a Senior Research Software Engineer (Machine Learning), working on the NERC funded Morphocam project. This project seeks to develop and release machine learning/AI tools to enable precise, metrics measurements to be made on camera trap images of wild animals. This is fundamentally a challenging problem because the 2D images lack depth. Utilizing advances in computer vision tools (e.g. foundational vision transformers), it is possible to “lift” 2D images to 3D. By combining these tools with field captured ground-truth data (e.g. with stereo photogrammetry or LIDAR) we aim to develop a software tool and API that can be used by biologists to obtain metric measurements of animal size and shape, and build deformable 3D meshes, as well as to estimate the distance from camera to the detected animal. Such a tool will revolutionize camera trap imagery analyses by allowing non-contact measurements of animal morphometrics which can provide insights on body condition, growth and aid visual reidentification while also facilitating distance sampling for population size estimation. As a Senior Research Sofware Engineer (Machine Learning), you will research, adapt and exploit existing deep learning models and frameworks to build an efficient and user-friendly processing pipeline. You will need extensive experience in machine learning frameworks (e.g. pytorch/tensorflow) and ML-ops for scaling systems into production. You will need to be able to communicate well and work easily with domain users (e.g. field biologists) to understand their needs and problems. You will be independent and self-driven, with a clear approach to project management and delivery. You will also have a strong publication record with a strong ambition towards to top-tier publications and dataset releases. This post may be underfilled at Grade 7. Responsibilities/duties  Develop and research machine learning/computer vision frameworks for camera trap analysis  Build and scale machine learning pipelines to achieve the research objectives  Share responsibility for shaping the research project’s milestones and outputs  Regularly write research articles at a national level for peer-reviewed journals, book chapters, and reviews. Present papers at national conferences, and lead seminars to disseminate research findings  Participate in regular project meetings and workshops with partners and funders  Write reports and documents for funders and project partners  Collaborate closely with researchers and academics from different departments Selection criteria Essential  Hold a relevant Ph.D/D.Phil  Publication record and familiarity with the existing literature and research in the field.  Experience in software engineering development  Have significant research experience in computer vision and deep learning or similar 2  Possess sufficient specialist knowledge in the discipline to develop research projects and methodologies  Ability to independently plan and manage a research project, including a research budget Desirable  Post-qualification research experience  Have experience of scaling machine learning (MLOps)  Experience with sensor design and deployment  Experience on working with wildlife datasets  Experience with open-source research tool development e.g. through Github package releases  Experience of supervising staff, especially across different disciplines/departments Pre-employment screening Standard checks If you are offered the post, the offer will be subject to standard pre-employment checks. You will be asked to provide: proof of your right-to-work in the UK; proof of your identity; and (if we haven’t done so already) we will contact the referees you have nominated. You will also be asked to complete a health declaration so that you can tell us about any health conditions or disabilities for which you may need us to make appropriate adjustments. Please read the candidate notes on the University’s pre-employment screening procedures at: https://www.jobs.ox.ac.uk/pre-employment-checks About the University of Oxford Welcome to the University of Oxford. We aim to lead the world in research and education for the benefit of society both in the UK and globally. Oxford’s researchers engage with academic, commercial and cultural partners across the world to stimulate high-quality research and enable innovation through a broad range of social, policy and economic impacts. We believe our strengths lie both in empowering individuals and teams to address fundamental questions of global significance, while providing all our staff with a welcoming and inclusive workplace that enables everyone to develop and do their best work. Recognising that diversity is our strength, vital for innovation and creativity, we aspire to build a truly diverse community which values and respects every individual’s unique contribution. While we have long traditions of scholarship, we are also forward-looking, creative and cutting-edge. Oxford is one of Europe's most entrepreneurial universities and we rank first in the UK for university spin-outs, and in recent years we have spun out 15-20 new companies every year. We are also recognised as leaders in support for social enterprise. Join us and you will find a unique, democratic and international community, a great range of staff benefits and access to a vibrant array of cultural activities in the beautiful city of Oxford. For more information, please visit www.ox.ac.uk/about/organisation. 3 Department of Computer Science The Department of Computer Science was established in 1957, making it one of the longestestablished Computer Science departments in the country. It is one of the UK’s leading Computer Science Departments (ranked first in a number of international rankings). Our Computer Science and Informatics submission to the UK Research Excellence Framework (REF) in December 2021 resulted in 81% of research activity ranked as 4* (world-leading) and the rest ranked as 3* (internationally excellent). A significant majority of the Department are active in externally sponsored research, with both government and industrial funding. At present, there are 74 members of academic staff and 100 research staff. The Department has close links with government, industry, and other departments within the University. Among the latter are Mathematics, Engineering, Physics, Statistics and life sciences. The Department is housed across multiple sites within the University’s South Parks Road Science Area, facilitating strong collaborative links with research groups and institutes in closely allied areas (including the Oxford Internet Institute and the Oxford e-Research Centre). At present, the Department holds over £75m in external funding of which £58m is research. Research in the Department is currently managed in ten themes:  Algorithms & Complexity Theory, led by Professor Leslie Ann Goldberg, focusses on determining the inherent difficulty of computational problems, classifying problems according to this inherent difficulty, and designing and analysing algorithms that use computational resources as efficiently as possible;  Artificial Intelligence & Machine Learning, led by Professor Michael Wooldridge, focuses on theoretical foundations of AI, multiagent systems, deep learning, reinforcement learning ,and computational linguistics;  Automated Verification, led by Professor Marta Kwiatkowska, investigates theory and practice of formal verification and correct-by-construction synthesis for software and hardware systems;  Computational Biology & Health Informatics, led by Professor Blanca Rodriquez , is concerned with computational approaches for biomedical research and healthcare innovation;  Human-Centred Computing, led by Professor Nigel Shadbolt, includes human-computer interaction, social computing, and the worldwide web;  Data, Knowledge and Action, led by Professor Ian Horrocks, includes databases, knowledge representation and reasoning;  Programming Languages, led by Professor Sam Staton, includes functional programming, program analysis, and programming language foundations;  Quantum, led by Professor Jonathan Barrett, focusses on quantum computing including quantum software, causality in quantum theory, quantum cryptography and foundations of quantum computing;  Security, led by Professor Ivan Martinovic, specialises in cybersecurity, protocol analysis, systems security, trusted computing, and networking.  Systems, led by Professor Niki Trigoni, focusses especially on cyber physical systems. We plan to substantially broaden our research in systems to complement our existing research areas. For more information, please visit: http://www.cs.ox.ac.uk/. The Department of Computer Science holds a bronze Athena Swan award to recognise advancement of gender equality: representation, progression and success for all. 4 7 The Mathematical, Physical, and Life Sciences Division (MPLS) The Mathematical, Physical, and Life Sciences (MPLS) Division is one of the four academic divisions of the University. Oxford is widely recognised as one of the world's leading science universities and the MPLS Division is home to our non-medical sciences, with 9 academic departments that span the full spectrum of the mathematical, computational, physical, engineering and life sciences, and undertake both fundamental research and cutting-edge applied work. Our research tackles major societal and technological challenges – whether developing new energy solutions or improved cancer treatments, understanding climate change processes, or helping to preserve biodiversity, and is increasingly focused on key interdisciplinary issues. We collaborate closely with colleagues in Oxford across the medical sciences, social sciences and humanities, and with other universities, research organisations and industrial partners across the globe in pursuit of innovative research geared to address critical and fundamental scientific questions. MPLS is proud to be the home of some of the most creative and innovative scientific thinkers and leaders working in academe. Our senior researchers have been awarded some of the most significant scientific honours and we have a strong tradition of attracting and nurturing the very best early career researchers who regularly secure prestigious fellowships and faculty positions. MPLS continues in its work to support diversity in its staffing, seeing that it will bring benefits to all, and we are pleased to note that all academic departments in the Division hold Athena Swan Awards. We have around 7,000 full and part-time students (including approximately 3,500 graduate students) and play a major role in training the next generation of leading scientists. Oxford's international reputation for excellence in teaching is reflected in its position at the top of the major league tables and subject assessments. MPLS academics educate students of high academic merit and potential from all over the world. Through a mixture of lectures, practical work and the distinctive college tutorial system, students develop their ability to solve diverse mathematical, scientific and engineering problems. MPLS is dedicated to bringing the wonder and potential of science to the attention of audiences far beyond the world of academia. We have a strong commitment to supporting public engagement in science through initiatives including the Oxford Sparks portal (www.oxfordsparks.ox.ac.uk) and a large variety of outreach activities; these are crucial activities given so many societal and technological issues demand an understanding of the science that underpins them. We also bring the potential of our scientific efforts forward for practical and beneficial application to the real world and our desire, aided by the work of Oxford University Innovation and Oxford Sciences Innovation, is to link our best scientific minds with industry and public policy makers. For more information about the MPLS division, please visit: www.mpls.ox.ac.uk How to apply Applications are made through our online recruitment portal. Information about how to apply is available on our Jobs website https://www.jobs.ox.ac.uk/how-to-apply. Your application will be judged solely on the basis of how you demonstrate that you meet the selection criteria stated in the job description. As part of your application you will be asked to provide details of two referees and indicate whether we can contact them now. 5 You will be asked to upload a CV and a supporting statement. The supporting statement must explain how you meet each of the selection criteria for the post using examples of your skills and experience. This may include experience gained in employment, education, or during career breaks (such as time out to care for dependants) Please upload all documents as PDF files with your name and the document type in the filename. All applications must be received by midday UK time on the closing date stated in the online advertisement. Information for priority candidates A priority candidate is a University employee who is seeking redeployment because they have been advised that they are at risk of redundancy, or on grounds of ill-health/disability. Priority candidates are issued with a redeployment letter by their employing department(s). If you are a priority candidate, please ensure that you attach your redeployment letter to your application (or email it to the contact address on the advert if the application form used for the vacancy does not allow attachments). If you need help Application FAQs, including technical troubleshooting advice is available at: https://staff.web.ox.ac.uk/recruitment-support-faqs Non-technical questions about this job should be addressed to the recruiting department directly (hr@cs.ox.ac.uk ) To return to the online application at any stage, please go to: www.recruit.ox.ac.uk. Please note that you will receive an automated email from our online recruitment portal to confirm receipt of your application. Please check your spam/junk mail if you do not receive this email. Important information for candidates Data Privacy Please note that any personal data submitted to the University as part of the job application process will be processed in accordance with the GDPR and related UK data protection legislation. For further information, please see the University’s Privacy Notice for Job Applicants at: https://compliance.admin.ox.ac.uk/job-applicant-privacy-policy. The University’s Policy on Data Protection is available at: https://compliance.admin.ox.ac.uk/data-protection-policy. The University’s policy on retirement The University operates an Employer Justified Retirement Age (EJRA) for very senior research posts at grade RSIV/D35 and clinical equivalents E62 and E82 of 30 September before the 70th birthday. The justification for this is explained at: https://hr.admin.ox.ac.uk/the-ejra. For existing employees on these grades, any employment beyond the retirement age is subject to approval through the procedures: https://hr.admin.ox.ac.uk/the-ejra. There is no normal or fixed age at which staff in posts at other grades have to retire. Staff at these grades may elect to retire in accordance with the rules of the applicable pension scheme, as may be amended from time to time. 6 Equality of opportunity Entry into employment with the University and progression within employment will be determined only by personal merit and the application of criteria which are related to the duties of each particular post and the relevant salary structure. In all cases, ability to perform the job will be the primary consideration. No applicant or member of staff shall be discriminated against because of age, disability, gender reassignment, marriage or civil partnership, pregnancy or maternity, race, religion or belief, sex, or sexual orientation. Benefits of working at the University Employee benefits University employees enjoy 38 days’ paid holiday, generous pension schemes, flexible working options, travel discounts including salary sacrifice schemes for bicycles and electric cars and other discounts. Staff can access a huge range of personal and professional development opportunities. See https://hr.admin.ox.ac.uk/staff-benefits Employee Assistance Programme As part of our wellbeing offering staff get free access to Health Assured, a confidential employee assistance programme, available 24/7 for 365 days a year. Find out more https://staff.admin.ox.ac.uk/health-assured-eap University Club and sports facilities Membership of the University Club is free for University staff. It offers social, sporting, and hospitality facilities. Staff can also use the University Sports Centre on Iffley Road at discounted rates, including a fitness centre, powerlifting room, and swimming pool. See www.club.ox.ac.uk and https://www.sport.ox.ac.uk/. Information for staff new to Oxford If you are relocating to Oxfordshire from overseas or elsewhere in the UK, the University's Welcome Service includes practical information about settling in the area, including advice on relocation, accommodation, and local schools. See https://welcome.ox.ac.uk/ There is also a visa loan scheme to cover the costs of UK visa applications for staff and their dependants. See https://staffimmigration.admin.ox.ac.uk/visa-loan-scheme Family-friendly benefits We are a family-friendly employer with one of the most generous family leave schemes in the Higher Education sector. Our Childcare Services team provides guidance and support on childcare provision, and offers a range of high quality childcare options at affordable prices for staff. In addition to 5 University nurseries, we partner with a number of local providers to offer in excess of 450 full time nursery places to our staff. Eligible parents are able to pay for childcare through salary sacrifice, further reducing costs. See https://childcare.admin.ox.ac.uk/ . We also subscribe to the Work+Family Space, a service that provides practical advice and support for employees who have caring responsibilities for dependants of all types. See https://hr.admin.ox.ac.uk/my-family-care Supporting disability and health-related issues (inc menopause) We are committed to supporting members of staff with disabilities or long-term health conditions, including those experiencing negative effects of menopause. Information about the University’s Staff Disability Advisor, is at https://edu.admin.ox.ac.uk/disability-support. For information about how we support those going through menopause see https://hr.admin.ox.ac.uk/menopause-guidance 7 Staff networks The University has a number of staff networks including for research staff, BME staff, LGBT+ staff, disabled staff network and those going through menopause. Find out more at https://edu.admin.ox.ac.uk/networks The University of Oxford Newcomers' Club The University of Oxford Newcomers' Club is run by volunteers that aims to assist the partners of new staff settle into Oxford, and provides them with an opportunity to meet people and make connections in the local area. See www.newcomers.ox.ac.uk. Research staff The Researcher Hub supports all researchers on fixed-term contracts. They aim to help you settle in comfortably, make connections, grow as a person, extend your research expertise and approach your next career step with confidence. Find out more https://www.ox.ac.uk/research/supportresearchers/researcher-hub Oxford’s Research Staff Society is a collective voice for our researchers. They also organise social and professional networking activities for researchers. Find out more https://www.ox.ac.uk/research/support-researchers/connecting-other-researchers/oxfordresearch-staff-society . 8 """^^ . "OxPoints"@en . "Fax"@en . . . . . . . "OpenStreetMap feature identifier" . . . . . . "false"^^ . "notation"@en . "2024-07-15T12:00:00+01:00"^^ . . . . "email"@en . . . . _:N0af56aaae7734b85bc528bdbc92f1508 . "telephone"@en . . "country name"@en . . . . . . "173378 Job description and selection criteria" . "postal code"@en . "Turtle description of Research Software Engineer (ML)" . . . . . "application/xhtml+xml" . . _:N4bc8bc916c9c4033af45b99da5b65598 "United Kingdom" . "subOrganization of"@en . "page" . . _:Na5d9534b36874c589b3ac76ba70ea8a5 "OX1 2JD" . "Past vacancies at the University of Oxford" . . . . "Computer Science - Wolfson Building, Parks Road, Oxford." . . "Computing Lab" . . "Old OLIS code" . . . . . _:Na5d9534b36874c589b3ac76ba70ea8a5 "United Kingdom" . . . . _:Na5d9534b36874c589b3ac76ba70ea8a5 . . . "application/rdf+xml" . "valid through (0..1)"@en . "Computing Lab"^^ . . "Format"@en . . . . . "text/n3" . "longitude" . . _:N5a9dd89ba85e48d1aeabc4064b0d8579 . "address"@en . _:N5a9dd89ba85e48d1aeabc4064b0d8579 . "OxPoints"@en . "Address"@en . _:N4bc8bc916c9c4033af45b99da5b65598 "OX1 3QD" . . """

We are hiring a Senior Research Software Engineer based at the Department of Computer Science, under the supervision of Professor Andrew Markham. This is a cross-disciplinary project between the Departments of Computer Science and Biology and the successful post-holder will be working on the NERC funded Morphocam project. This project seeks to develop and release machine learning/AI tools to enable precise, metrics measurements to be made on camera trap images of wild animals. 

 

As a Senior Research Sofware Engineer (Machine Learning), you will research, adapt and exploit existing deep learning models and frameworks to build an efficient and user-friendly processing pipeline. You will need extensive experience in machine learning frameworks (e.g. pytorch/tensorflow) and ML-ops for scaling systems into production. You will need to be able to communicate well and work easily with domain users (e.g. field biologists) to understand their needs and problems. You will be independent and self-driven, with a clear approach to project management and delivery. You will also have a strong publication record with a strong ambition towards to top-tier publications and dataset releases.

 

You will hold a relevant Ph.D/D.Phil  and possess experience in software engineering development. Research experience in computer vision and deep learning or similar is required. 

Applicants will be required to upload a supporting statement, setting out how you meet the selection criteria. 

 

The closing date for applications is 12 noon on 15 July 2024. Interviews are expected to be held in July.  

 

We are a Stonewall Top 100 Employer, Living Wage and Mindful Employer, holding an Athena Swan Bronze Award, HR excellence in Research and Race Equality Charter Bronze Award.

 

Our staff and students come from all over the world and we proudly promote a friendly and inclusive culture. Diversity is positively encouraged, through diversity groups and champions, for example http://www.cs.ox.ac.uk/aboutus/women-cs-oxford/index.html , as well as a number of family-friendly policies, such as the right to apply for flexible working and support for staff returning from periods of extended absence, for example shared parental leave.

 

Demonstrating a commitment to provide equality of opportunity. We would particularly welcome applications from women and black and minority ethnic applicants who are currently under-represented within the Computer Science Department. All applicants will be judged on merit, according to the selection criteria.
"""^^ . "Computer Science Library" . "extended address"@en . . . . . . . . "text/turtle" . . "40006001"^^ . "logo" . . . . "51.75997"^^ . "Source"@en . . "a un site"@fr . "library description page" . "OLIS code" . "name" . . . . "2024-06-17T09:00:00+01:00"^^ . "value" . . _:N8c48a442b81e4f308b874d75770a4729 . . . . . "site principal"@fr . "Research Software Engineer (ML)" . . "has primary place" . . _:N3be0ae7459e0464dafc36181f66f5d7d "United Kingdom" . . . . . . . _:N8c48a442b81e4f308b874d75770a4729 . . . . . . "Department of Computer Science" . "COMDL"^^ . . . . "image" . . . . "2024-07-15T12:00:00+01:00"^^ . . . "NTriples description of Research Software Engineer (ML)" . _:Na5d9534b36874c589b3ac76ba70ea8a5 "University of Oxford" . . "Subject"@en . "Department of Computer Science" . "false"^^ . "occupies" . "has max currency value (1..1)"@en . . . . "university" . "Oxford, University of" . . "University of Oxford" . . . . . "University of Oxford" . "COM" . . "Wolfson Building" . . _:N8c48a442b81e4f308b874d75770a4729 "+44-1865-270708" . "primary Site"@en . . . . _:N4bc8bc916c9c4033af45b99da5b65598 "Room 240, Wolfson Building" . _:N3be0ae7459e0464dafc36181f66f5d7d "OX1 3QD" . "library" . . "tiene sede en"@es . . . . . . "COM"^^ . . . . . "Grade 8: £45,585 - £54,395 p.a. with the potential to under-fill at Grade 7 with salaries in the range of £36,024 - £44,263 p.a." . "8" . "comment" . """We are hiring a Senior Research Software Engineer based at the Department of Computer Science, under the supervision of Professor Andrew Markham. This is a cross-disciplinary project between the Departments of Computer Science and Biology and the successful post-holder will be working on the NERC funded Morphocam project. This project seeks to develop and release machine learning/AI tools to enable precise, metrics measurements to be made on camera trap images of wild animals. As a Senior Research Sofware Engineer (Machine Learning), you will research, adapt and exploit existing deep learning models and frameworks to build an efficient and user-friendly processing pipeline. You will need extensive experience in machine learning frameworks (e.g. pytorch/tensorflow) and ML-ops for scaling systems into production. You will need to be able to communicate well and work easily with domain users (e.g. field biologists) to understand their needs and problems. You will be independent and self-driven, with a clear approach to project management and delivery. You will also have a strong publication record with a strong ambition towards to top-tier publications and dataset releases. You will hold a relevant Ph.D/D.Phil and possess experience in software engineering development. Research experience in computer vision and deep learning or similar is required. Applicants will be required to upload a supporting statement, setting out how you meet the selection criteria. **The closing date for applications is 12 noon on 15 July 2024.** Interviews are expected to be held in July. **We are a Stonewall Top 100 Employer, Living Wage and Mindful Employer, holding an Athena Swan Bronze Award, HR excellence in Research and Race Equality Charter Bronze Award.** Our staff and students come from all over the world and we proudly promote a friendly and inclusive culture. Diversity is positively encouraged, through diversity groups and champions, for example http://www.cs.ox.ac.uk/aboutus/women-cs-oxford/index.html , as well as a number of family-friendly policies, such as the right to apply for flexible working and support for staff returning from periods of extended absence, for example shared parental leave. Demonstrating a commitment to provide equality of opportunity. We would particularly welcome applications from women and black and minority ethnic applicants who are currently under-represented within the Computer Science Department. All applicants will be judged on merit, according to the selection criteria. """ . _:N0af56aaae7734b85bc528bdbc92f1508 "+44-1865-270000" . . "has exact match"@en . . . . _:Na5d9534b36874c589b3ac76ba70ea8a5 "Oxford" . _:N4bc8bc916c9c4033af45b99da5b65598 . "RDF/XML description of Research Software Engineer (ML)" . . _:N4bc8bc916c9c4033af45b99da5b65598 . "application/pdf" . . . . . "Computer Science Library" . "sous-Organization de"@fr . . . . . . "32320013"^^ . "ha sede"@it . "has currency (1..1)"@en . "depiction" . "text/html" . "false"^^ . . . . "homepage" . _:N3be0ae7459e0464dafc36181f66f5d7d . . "Unit price specification"@en . . . . . . _:N0af56aaae7734b85bc528bdbc92f1508 . "Is Part Of"@en . "has min currency value (1..1)"@en . "account" . . "Description of Research Software Engineer (ML)" . . . "latitude" . . . "173378"^^ . . . . . . . "HR Coordinator" . . _:N4bc8bc916c9c4033af45b99da5b65598 "Oxford" . "-1.258246"^^ . "36024"^^ . . . "Notation3 description of Research Software Engineer (ML)" . "License"@en . . . . . . . . "text/plain" . . .